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Graph-in-Graph (GiG): Learning interpretable latent graphs in non-Euclidean domain for biological and healthcare applications
In this work, we propose Graph-in-Graph (GiG), a neural network architecture for protein classification and brain imaging applications that exploits the graph representation of the input data samples and their latent relation.
Peri-Diagnostic Decision Support Through Cost-Efficient Feature Acquisition at Test-Time
Computer-aided diagnosis (CADx) algorithms in medicine provide patient-specific decision support for physicians.
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